Noise in video equipment may arise from electrical distortions and interference created by power supply hum interactions between internal electrical components, etc. Noise may also be in the form of distractions from the pure signal transference, modification or amplification. For example, conversion between analog and digital domains leads to noise. Any of these factors or a combination of them, can combine to adversely affect the signal to noise ratio (SNR).
Although some noise is found in all video systems, the lower the noise rating of a component the better. Noise can be a problem if one wants to attain enhanced detail. At some point, the signal actually is lower in power than the noise itself (the noise floor), resulting in the true signal being obscured. The lower the noise floor of a component, the smaller a signal the system can cleanly produce and the more detail the system may have at low levels. Stated in other words, the “noise floor” is the point at which the volume or power of noise is greater than the volume or power of an intended and desired signal effectively covering up and obscuring that signal.
Various noise reduction techniques have been developed to improve the image quality of noisy video. Typically, these noise reduction techniques increase the SNR by smoothing the image sequence in the temporal or spatial domains. The amount of smoothing should be proportional to the noise floor of the incoming image sequence. Too much temporal smoothing results in motion blur, and too much spatial smoothing results in loss of detail.
Smoothing techniques are “linear” and are used to mitigate noise that arises from Gaussian noise injection. Non-linear techniques, such as a median filter, are used to mitigate impulse noise, such as the noise that results from spikes on the transmission line.